Experimental and machine learning research on a multi-functional Trombe wall system
Küçük Resim Yok
Tarih
2024
Dergi Başlığı
Dergi ISSN
Cilt Başlığı
Yayıncı
Inderscience Enterprices Ltd.
Erişim Hakkı
info:eu-repo/semantics/restrictedAccess
Özet
Performance prediction tools can assist architects and engineers in designing and sizing TWs without the extensive effort, time, and costs associated with experimental evaluations. This study aims to develop an artificial neural network (ANN) model for predicting the performance of a multi-functional TW by using 57 experimental datasets and the Levenberg-Marquardt algorithm as the training algorithm. The developed model was found to be capable of TW performance prediction with error rates < 0.23%. The performance parameters for the ANN model, namely the mean squared error (MSE) and the coefficient of determination (R), were calculated to be 0.034 and 0.99917, respectively.
Açıklama
Anahtar Kelimeler
Trombe wall; heating; buildings; artificial neural network; ANN; Levenberg-Marquardt; global warming; sustainable architecture
Kaynak
International Journal of Global Warming
WoS Q Değeri
N/A
Scopus Q Değeri
N/A
Cilt
33
Sayı
4
